Can we trust biomarkers identified using different non-targeted metabolomics platforms? Multi-platform, inter-laboratory

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ORIGINAL ARTICLE

Can we trust biomarkers identified using different non‑targeted metabolomics platforms? Multi‑platform, inter‑laboratory comparative metabolomics profiling of lettuce cultivars via UPLC‑QTOF‑MS Carlos J. García1   · Xiao Yang2,3 · Danfeng Huang3 · Francisco A. Tomás‑Barberán1 Received: 13 April 2020 / Accepted: 20 July 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020

Abstract Introduction  Data analysis during UPLC-MS non-targeted metabolomics introduces variation as different manufacturers use specific algorithms for data treatment and this makes untargeted metabolomics an application for the discovery of new biomarkers with low confidence in the reproducibility of the results under the use of different metabolomics platforms. Objectives  This study compared the ability of two platforms (Agilent UPLC-ESI-QTOF-MS and Waters UPLC-IMS-QTOFMS) to identify biomarkers in butterhead and romaine lettuce cultivars. Methods  Two case studies by different metabolomics platforms: (1) Waters and Agilent datasets processed by the same data pre-processing software (Progenesis QI), and (2) Datasets processed by different data pre-processing software. Results  A higher number of candidate biomarkers shared between sample groups in case 2 (101) than in case 1 (26) was found. Thirteen metabolites were common to both cases. Romaine lettuce was characterised by phenolic compounds including flavonoids, hydroxycinnamate derivatives, and 9-undecenal, while Butterhead showed sesquiterpene lactones and xanthosine. This study demonstrates that high percentages of the most discriminatory entities can be obtained by using the manufacturers’ embedded pre-processing software and following the recommended processing data guidelines using commercial software to normalise the data matrix. Keywords  Plant metabolomics · Lettuce biomarkers · Metabolic profiling · Multivariate analysis · Multi-platform analysis Carlos J. García and Xiao Yang have contributed equally to this work.

1 Introduction

Electronic supplementary material  The online version of this article (https​://doi.org/10.1007/s1130​6-020-01705​-y) contains supplementary material, which is available to authorized users.

Plant metabolomics can reveal altered metabolite expression levels and changes in metabolic pathways in response to disturbances in biotic and abiotic factors within biological systems (Fiehn 2002; Shulaev et al. 2008). Advanced analytical platforms such as ultra-performance liquid chromatography coupled with quadrupole/time-of-flight mass spectrometry (UPLC-QTOF/MS) and ion mobility (IMS) IMS-QTOF have become the preferred technologies for plant metabolomics studies due to their ability to rapidly separate metabolites and enable high-throughput detection of small molecules, including secondary metabolites (Gika et al. 2014; Rochat 2016). UPLC-QTOF/MS is the most widely used platform for plant metabolomics because of its rapid scan rate and high-resolution mass accuracy. The most advanced technique, UPLC-IMS-QTOF/MS, separates